1. Introduction¶
This is an analysis
Will be performed by:
- looking at the dataset independently
- cross-referencing the police killing dataset with demographic data on the state and the CBSA (core based statistical areas, a collection of interlinked counties such as a metropolitan area) to determine {THE}
The goal of this analysis is try to establish what are the statistical factors which {INFLUENCE} the number of police shooting and {WHTEHRT}
¶
2. Overview of the dataset¶
In this part we'll analyze each relevant variable in the main dataset.
Additionally US census data will be used calculate per capita shooting rates for each race for each state and the country as whole.
The insights gained in this part will be used to determine areas to focus on in the main sections.
We can see that native americans and especially black people are severely overrepresnted. The police shooting rate for black people is two times higher than would be expected based on their population. On the other hands white and asian people are much less likely to be shot.
There are two Socio economic and demographic factors, e.g. Black people are more likely to be poor and thereforce are more likely to engaged in activities which signficantly increase the likelyhood of being shoot by police, they are more likely to live in areas where police behaviour is less controlled and police shootings are more frequent etc.
Black and native American people are targeted more often due to racial prejudice.
Without performing further analysis we can't answer which of these explanations is more accurate.main possible explanations for this:
Then map above compares the number police shootings per capita across different states. The drop down in the top right might be used to select different races. When a specific race is selected the map show by how much are different racial groups over/under represented compared to the general state population.
Looking at the state level data we can see that:
- Gennerally north-eastern states have the lowest incidency of police shootings.
- Shootings of black people (relative to population are most frequent in midwestern and western states), the only state were black people are significantly overrepresnted in the east is West Virginia.
The graph above shows how the overrepresnation of black people relate the black population in a state.
The states to right have a larger black population (e.g. in Washington DC close to 50%n of all people are black).
The Y axis show the ratio between the black population in a state and the proportion of victims who are black. e.g. in the topmost state, Utah black people make up only 1.3% of the population but about 7.2% of all victims are black.
We can conclude from this chart that the higher proportion of black people live in a state the less likely are they to be show
This finding is quite interesting, while we can just conclusions but one possible explanation is that in areas where black people might make up a higher proportion of of law enforcement agencies they are less likely to be shot than in those where black populations are small.
This would indicate that racial prejudice might be one of the main reasons of this relationship.
Interestingly if we look at Hispanic population the relationship is inverse. The more Hispanic people live in a state there more likely they are to be overrepresented. This might indicate the an increase in police shotings might be community realated, however this requires further investigation.
2.4.1 Threat Type By Race¶
In this section we'll try to examine the circumstances under the victims we killed and we'll check whether they vary signficantly between different races.
We can see that the reported threat type does indeed vary between races, for instance:
It seems that black people are signficantly more likely to be shot while shooting a firearm. This is likely an argument against the racial prejudice hypothesis we've expressed previously since shooting is gennerally the most serious threat and the one most likely to be met with deadly force regardless of the shooter's race.
In the main chart we've noticed that there are slighly more incidents where black people were shot but there was no reported threat type compared to other races. However this does not appear to be significant, but it might be worth examining it further as it likely indicates that these people might have been shot without sufficient cause.
Another interesting observation is that hispanic people are less likely to be firing a gun when shot. This also something which should be investigated further.
This suggests that police officers are less likely to shot white people unless they are carrying some oo
The fact that Hispanic people are more likely to be shot while not firing a gun seems to be mostly explained by them being more likely to have knives.
1.3 Analysis¶
After examining the dataset and performing some basic hypothesis testing we've found that there are some significant differences between the characteristics of victims depending on their race and age:
- Black people are more likely to be killed when after shooting or actively attacking someone than other group
- Hispanic and other people are more likely to be killed when not armed with a firearm than black or white people
- Killings of white individuals are more likely to be related to mental health issues
- Killings of black people are more likely to have no determined reason than for other groups
- White people are significantly less likely to be killed when the officer is wearing a body camera
- Non-white people are significantly more likely to be killed when unarmed
- People who are 45 or older are more likely to be killed while pointing a firearm
However we can't explain whether these relationships exist due to some underlying reason (e.g. systemic discrimination or biases of the law enforcement agents, socioeconomic differences between racial groups etc.) without additional data. This is something that needs to be investigated further.
However even if we were able to provide a more reliable explanation for these relationships that does not mean that we will be able to derive actionable decisions for the United States Department of Justice. Solving them might require an enacment of complex socioecnomic policies which is not something the state department is in control.
Actionable Decisions¶
One other important aspect that we must take into account is that while all police shootings are regretable the majority of them are justifiable in the sense that the victim was shot while commiting a violent crime and threatening the life and safery of other individuals and/or police officers.
While it's possibly that the prior training etc. of police officers to handle such situations using less lethal methods can possibly decrease the number of deaths this is not something wen can analyze using the data we have.
Instead we'll focus on demographic, social, economic and other macro factors which can be used to explain the varying levels of police shootings between differents states to: 1. Determine the factors which explain the variance in police shootings. 2. Find factors which can be influenced by Federal and local governments.
This might allow police deparments in different states to adopt policies, training standards etc. from other jurisdictions which is potentiall a relatively straighforward way to decrease the incidence of police shootings.
1.3.1 Explaining Differences Between States:¶
One possible approach could be to try and find demographically similar US states which have signficantly different numbers of shootings per capita. If such states exist we can try to find whether this can be explained by some other variable or attribute which could be theoretically influenced by local or state governments.
1.3 Analysis¶
Let's build a statistical model to try and determine which of the demographic and other variables are best at explaining the variance in police shootings between different states.
We can't use Random Forest due to the low number of observations which would likely result in overfitting.
Multiple linear regression is also possibly not the best option due to the higher number of dependent variables in relation to the number of observations.
Let's look at the correlation between dependent variables before we chose a model:
1.3.3 Interpreting Model Results¶
Any conclusions we make based on these results are obviously should be taken with a grain of salt however they do show some possibly suprising finding:
Racial diversity/proportion of non-white population has no influence on the number of shootings per capita.
However population density and conentration seem to be important factors. Specifically the proportion of people living in multi-unit housing units (apartments) seems to be the strongest predictor. There are likely several non straigforward interpretations of this however in combination with population density this might imply that:
- police officers tend to behave different depending how likely other people and bystanders in general are to witness their actions.
- Also it's possible that they feel less safe in lense densely populated areas because it might take longer for other officers to reach them.
- People shot by police are more likely to die if it occurs in areas with poor coverage by emergency services and it takes a long time for them to arrive.
We can't test the validity of any of these hypothesis but it might be worth examining them further because they all seem to be highly actionable (improving police training, strategies for acting around dangerous individuals like waiting for backup etc.)
Homocide rate seems to have no effect on the number of police shooting while the amount spent per capita on policing in the state is a relatively strong predictor.
this implies that there is not link between the general level of extreme violence in the state and the number of police shootings. This is highly concerned since using deadly force is only justifiable when the life of the officer or somebody else is in danger. However there seems to be no relationship between actual likelyhood of a life threatening event occuring the decision by a law enforcement officer to use deadly force.
This is something that certainly should be investigated further and is also possibly highly actionable. Especially because certain states handle this much better (like New York) and their practices might be applied in states which handle it much worse like New Mexico.
High police spending seems to have a moderate effect on the incidence of police shooting combined with the homocide statistics this is also highly concerning. Increased spending on police, in this case at least, seems to produce a more negative outcome. It's hard to determine why this might be the case. However it's possible that signicant proportions of funding might be missaolcated (e.g. spent on unncesary equipment etc.) and might better used to improve training. Even barring that it might mean that a smaller police presence might decrease the number of police shooting while have no effect on the murder rate (it's important to note that other crime statistics are not taken into account here).
Limitations¶
The core of the analysis is based on analyzing US states. This mean that the number of samples is quite and low and might be to low to for some mode. It might be worth going down a level or so and using Combined statistical area instead (collections of countries based on interconnected, ussually urban areas).
It would be a good idea to look at more variables like the number of police interactions and the liklyhood of them ending in a police shooting based on the target socio-economic status, race, mental state etc. and other factors like whether the officer is wearing a body camera, their training level etc. Of course such datasets are probably unobtanable without significant resources.